Parametric Growth Curve
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Stat > Reliability/Survival > Repairable System Analysis > Parametric Growth Curve

Use to perform a parametric analysis on a repairable system. Use either a power-law process or a homogeneous Poisson process to estimate the mean number of failures or the rate of occurrence of failure (ROCOF) over time.

If you have a column of data from more than one system, Minitab assumes that your data are from identical processes and provides a pooled growth curve estimate. In this case, Minitab tests for equal shapes or scales across these systems. See Test for equal shapes or scales.

If you provide a By variable or  two or more columns (exact data) or pairs of columns (interval data), Minitab will also compare across growth curves modeling the different processes. See Test for equal shapes or scales across growth curves.

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Data are exact failure/retirement times Choose if you have exact data.

Data are interval failure/retirement times Choose if you have interval data.

Variables/Start variables: Enter columns (one column per sample) containing the start times.

End variables: If you have interval repair times, enter columns (one column per sample) of end times.

Freq. columns (optional): Enter columns (one column per sample) of frequency data. The columns must contain positive integers (exact data) or nonnegative integers (interval data).

System ID (optional): Enter columns (one column per sample) to identify the systems. If a single response column represents more than one system, you must use a System ID column. This results in an additional test for equal shape parameters.

By variable: Check if all of the samples are stacked into one column and enter a column of grouping indicators.

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